The presently disclosed subject matter relates to enrolling and matching biometric data in a way that is easier to use, hence providing a more positive user experience than previous solutions. Previously, multiple collections of the same biometric data have been collected during an initial enrollment phase and may prevent enrollment if those multiple collections should prove, during the initial collection phase to be not sufficiently similar. Under certain circumstances this can make enrollment difficult or impossible for a user. Furthermore, even upon successful enrollment, the previous solutions typically fall into one of two categories.
In a first category, as an example, the enrollment data remains unchanged, i.e., is not tuned or modified, or is modified or tuned, once the initial enrollment is complete, but, e.g., for only a very short time, minutes or hours, and/or number of updates, e.g., 1-3 or so. A second category is where the enrollment data is allowed to change for the purposes of improving and/or augmenting the enrollment data for a stored enrollment template of the user's biometric data, without regard to time or effect, i.e., potentially ad infinitum. This latter case can actually be used by sophisticated spoofers to so modify the stored enrollment template to actually change the response to future matching efforts so much as to allow a completely different biometric image to be one that is authenticating access or use or whatever the biometric authentication is being used to authenticate.
Here, spoofing is used in a broader sense than the traditional meaning of attempting to defeat a biometric security system by using a false finger, e.g., with a facsimile of the actual user's biometric, or even removing the actual biometric from the user for use as an input of the biometric image to be compared with a stored enrollment template. Spoofing here also is meant to include any form of attempt at falsely indicating to the system that the image being received, purportedly, but not actually, from an authorized user, to compare with the stored enrollment template, actually matches a stored enrollment template for that authorized user. This can include, as discussed here, modifying the stored enrollment template over time to become a match for a false input image, i.e., one not actually associated with the actual authorized user.
One example of a fingerprint swipe sensor useful with the presently disclosed subject matter is described in U.S. Pat. No. 6,289,114 entitled Fingerprint-Reading System, issued to Mainguet on Sep. 11, 2011. This patent describes a system in which the surface area of the sensor is far smaller than the surface area of the fingerprint to be read. The reading is done when the sensor and the finger are in contact and in a relative motion of sliding of the sensor and the finger with respect to each other. The system reconstitutes a complete two dimensional image of some portion of the fingerprint from the two dimensional partial images given by the sensor during this motion. The manner in which the system reconstitutes a complete image of the fingerprint from the partial images given by the sensor is not described. Another example of a swiped sensor utilizing capacitive coupling through features of the biometric being imaged, e.g., fingerprint ridges and valleys, can be found in U.S. Pat. No. 7,099,496, issued to Benkley, on Aug. 29, 2006, entitled Fingerprint Sensing Systems and Methods, assigned to the assignee of the present application. A so called 2D placement sensor which can be utilized to image part of a finger to get a fingerprint image of a user for authentication by matching to a stored template can be seen in U.S. Pat. No. 5,515,738, issued to Tamori on May 14, 1996, entitled Piezoelectric Surface Pressure Input Panel, utilizing pressure sensing at individual pixel locations in a 2d placement grid array, and U.S. Pat. No. 6,862,942, issued to Kawahata on Mar. 8, 2005, entitled Surface Pressure Distribution Sensor, using a 2D capacitive sensor array.
By way of an example of previous solutions, U.S. Pat. No. 7,616,787, entitled Methods for Finger Biometric Processing and Associated Finger Biometric Sensors, issued to Boshra on Nov. 10, 2009, relates to a swipe type sensor for constructing and then matching biometric images using mosaics from images of small areas of the biometric object, such as horizontal “slices” if a fingerprint image, and/or employing internal image features (minutia), at the physical level. That is, the mosaics are fused at the physical level, which Boshra proposes to change to account for possible misalignments. Thus, Boshra represents an example of approaches to imaging a biometric object, such as a fingerprint, including sensing, image storing and subsequent image comparison with later sensed images. The ongoing update of a stored template as disclosed in Boshra, can be an ever evolving process. That is, as taught in Boshra and other examples, every time the biometric is sampled a new stored enrollment template is potentially created, i.e., modifications to the existing stored enrollment template can occur. As another example of a previous solution, U.S. Pat. No. 6,546,122, entitled Method for Combining Fingerprint Templates Representing Various Sensed Area of Fingerprint to Derive One Fingerprint Template Representing the Fingerprint, issued on Apr. 8, 2003 to Russo, also shows updating a stored enrollment template for future biometric data comparisons using the continuingly updated and stored template.
Standard enrollment using N swipes or touches on a fingerprint sensor, typically has required that the N swipes match each other, at least to some degree, e.g., by some statistical or other criteria of measurement. Such enrollment has relied on the user's natural usage tendencies to create or not create variance in the enrollment data. This has been without regard to sensing area or sensor type, e.g., a linear one dimensional sensor array, a two dimensional swiped sensor array or a two dimensional placement sensor array.
Such known enrollment systems and methods may mostly, but not entirely, apply to two dimensional placement sensor arrays, where the user places the biometric to be sensed and imaged, e.g., on the two dimensional sensor array without swiping. Such enrollment is then meant to capture at least some area of the biometric being sensed and imaged, e.g., the fingerprint of a finger. Depending on the type of sensor array being used, and particularly the size of the sensor array, especially the size in the direction essentially orthogonal to the swipe direction, i.e., along the width of the finger as an example, the sensor array may not be able to sense and image all of the biometric features. That is, all the ridges and valleys of a finger print for the finger that is on or swiping the sensor array. Even with a wider sensor array, the curvature of the biometric on the opposing edges can distort the sensor's detection of a ridge or a valley associated, e.g., with a given pixel location in a reconstructed image. Therefore, after an enrollment template for, e.g., the user's finger is sensed and stored for later comparison when the user again interacts with the sensor array, variations in the way the user interacts can cause false negative matches unwarrantedly denying the user the access sought and frustrating and annoying the user.
As an example, shifting and or rolling or tilting the finger in the vicinity of the sensor can expose areas to the sensor that may not have adequately been sensed before during enrollment, i.e., outside of a so-called “sweet spot” that the linear sensor or 2D swiped sensor or 2D placement sensor is designed and constructed to sense. This can be, e.g., generally on the flat portion of the finger tip portion of the finger, and can also depend on sensor area and the like. Thus the template that was sensed, e.g., in an authentication process, may be determined to be sufficiently different than the stored template stored in an enrollment process. This can result even if the great bulk of the scanned biometric does match the template in some regions, e.g., on one side of the “sweet spot,” but does not, e.g., on one side or the other of the sweet spot representing an imaging, e.g., of a portion of the finger on that side not ordinarily sensed in the enrollment process. Such areas, e.g., sides of edges of the biometric can exist that are sensed during a particular authenticating swipe or placement. They can be sensed during a misaligned placement or misaligned or mistimed swipe, etc. in the authentication process but not during the formation of the stored enrollment template, e.g., due to this variation in interaction by the user with the sensor array from when the enrollment template was created. A biometric authentication system and method is needed, therefore, that can address these causes for possible false negative denials of authentication and access or use because of a failure to match the stored biometric image template “sweet spot” or a significant portion of the “sweet spot.”